{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Metadata level success analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib import rc\n",
    "import pandas as pd\n",
    "\n",
    "# plot style\n",
    "sns.set_style('whitegrid')\n",
    "sns.set_style({'font.family': 'Times New Roman'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata = pd.read_csv(\"data/metadata_merged.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>publicationDate</th>\n      <th>publisher</th>\n      <th>subject</th>\n      <th>type</th>\n      <th>name</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/U3QJQZ</td>\n      <td>2020</td>\n      <td>harvard</td>\n      <td>Medicine; Health and Life Sciences</td>\n      <td>ORGANIZATIONS_INSTITUTIONS</td>\n      <td>Harvard Dataverse</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/6KEXM7</td>\n      <td>2020</td>\n      <td>harvard</td>\n      <td>Social Sciences</td>\n      <td>ORGANIZATIONS_INSTITUTIONS</td>\n      <td>Harvard Dataverse</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/EEUTHP</td>\n      <td>2019</td>\n      <td>harvard</td>\n      <td>Social Sciences</td>\n      <td>ORGANIZATIONS_INSTITUTIONS</td>\n      <td>Harvard Dataverse</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/WBI9RT</td>\n      <td>2015</td>\n      <td>harvard</td>\n      <td>Social Sciences</td>\n      <td>ORGANIZATIONS_INSTITUTIONS</td>\n      <td>Harvard Dataverse</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/N0PBQ9</td>\n      <td>2015</td>\n      <td>harvard</td>\n      <td>Social Sciences</td>\n      <td>ORGANIZATIONS_INSTITUTIONS</td>\n      <td>Harvard Dataverse</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi  publicationDate publisher  \\\n0  doi:10.7910/DVN/U3QJQZ             2020   harvard   \n1  doi:10.7910/DVN/6KEXM7             2020   harvard   \n2  doi:10.7910/DVN/EEUTHP             2019   harvard   \n3  doi:10.7910/DVN/WBI9RT             2015   harvard   \n4  doi:10.7910/DVN/N0PBQ9             2015   harvard   \n\n                              subject                        type  \\\n0  Medicine; Health and Life Sciences  ORGANIZATIONS_INSTITUTIONS   \n1                     Social Sciences  ORGANIZATIONS_INSTITUTIONS   \n2                     Social Sciences  ORGANIZATIONS_INSTITUTIONS   \n3                     Social Sciences  ORGANIZATIONS_INSTITUTIONS   \n4                     Social Sciences  ORGANIZATIONS_INSTITUTIONS   \n\n                name  \n0  Harvard Dataverse  \n1  Harvard Dataverse  \n2  Harvard Dataverse  \n3  Harvard Dataverse  \n4  Harvard Dataverse  "
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load success rate data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/aggregate_results_env.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "2085"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.doi.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>file</th>\n      <th>r32</th>\n      <th>r36</th>\n      <th>r40</th>\n      <th>result</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/XFQZI2</td>\n      <td>Condemnation.R</td>\n      <td>Error in eval(expr, envir, enclos) : could not...</td>\n      <td>Error in read.dta13('Condemnation.dta') :   co...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/WGPDBS</td>\n      <td>Replication_of_Figures.R</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_10_effect_of_winning_on_gov.R</td>\n      <td>Error in diag(vcovHC(DMareg, type = 'HC3')) : ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>Error in vcovHC(DMareg, type = 'HC3') : could ...</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_11_rd_placebo.R</td>\n      <td>Error in ggsave('placebo.pdf', plot = placebo,...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/BPON3K</td>\n      <td>fig_12_historical_trend.R</td>\n      <td>Error in ggsave('historical_trend.pdf', plot =...</td>\n      <td>success</td>\n      <td>success</td>\n      <td>success</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi                               file  \\\n0  doi:10.7910/DVN/XFQZI2                     Condemnation.R   \n1  doi:10.7910/DVN/WGPDBS           Replication_of_Figures.R   \n2  doi:10.7910/DVN/BPON3K  fig_10_effect_of_winning_on_gov.R   \n3  doi:10.7910/DVN/BPON3K                fig_11_rd_placebo.R   \n4  doi:10.7910/DVN/BPON3K          fig_12_historical_trend.R   \n\n                                                 r32  \\\n0  Error in eval(expr, envir, enclos) : could not...   \n1                                            success   \n2  Error in diag(vcovHC(DMareg, type = 'HC3')) : ...   \n3  Error in ggsave('placebo.pdf', plot = placebo,...   \n4  Error in ggsave('historical_trend.pdf', plot =...   \n\n                                                 r36  \\\n0  Error in read.dta13('Condemnation.dta') :   co...   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                                 r40  \\\n0                                                NaN   \n1                                            success   \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...   \n3                                            success   \n4                                            success   \n\n                                              result  success  \n0                                                NaN      NaN  \n1                                            success      1.0  \n2  Error in vcovHC(DMareg, type = 'HC3') : could ...      0.0  \n3                                            success      1.0  \n4                                            success      1.0  "
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "Total number of entries: 3695\nTotal number after bad DOIs are removed: 3695\nUnique DOIs: 1447\nSuccess: 1472 out of 3695 => 0.3983761840324763\nTIL: 0 out of 3695 => 0.0\nError: 2223 out of 3695 => 0.6016238159675237\n"
    },
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def make_autopct(values):\n",
    "    def my_autopct(pct):\n",
    "        total = sum(values)\n",
    "        val = int(round(pct*total/100.0))\n",
    "        return '{p:.2f}%  ({v:d})'.format(p=pct,v=val)\n",
    "    return my_autopct\n",
    "\n",
    "def get_success_rates(df):\n",
    "    print \"Total number of entries: \"+ str(len(df))\n",
    "    print \"Total number after bad DOIs are removed: \"+ str(len(df))\n",
    "    \n",
    "    print \"Unique DOIs: \"+ str(len(df['doi'].unique()))\n",
    "    \n",
    "    # calculate success\n",
    "    success = (df['result'] == 'success').sum()\n",
    "    print \"Success: \" + str(success)+ \" out of \" + str(len(df)) +\" => \"+ str(success*1.0/len(df))\n",
    "    \n",
    "    til = (df['result'] == 'time limit exceeded').sum()\n",
    "    print \"TIL: \" + str(til)+ \" out of \" + str(len(df)) +\" => \"+ str(til*1.0/len(df))\n",
    "    \n",
    "    error = len(df)-til-success\n",
    "    print \"Error: \" + str(error)+ \" out of \" + str(len(df)) +\" => \"+ str(error*1.0/len(df))\n",
    "    \n",
    "    return [til, error, success]\n",
    "\n",
    "def plot_code(df, plot_title, plot_name, aggregation=False):\n",
    "    labels = [\"Time Limit Exceeded\",'Error', 'Success']\n",
    "    if aggregation:\n",
    "        sizes = get_aggregated(df)\n",
    "    else:\n",
    "        sizes = get_success_rates(df)\n",
    "     \n",
    "    fig1, ax1 = plt.subplots()\n",
    "    plt.rcParams['font.size'] = 16\n",
    "    ax1.pie(sizes, labels=labels, autopct=make_autopct(sizes), startangle=40,  \\\n",
    "            textprops={'fontsize': 14},wedgeprops={'alpha':0.6})\n",
    "\n",
    "    #draw circle\n",
    "    centre_circle = plt.Circle((0,0),0.70,fc='white')\n",
    "\n",
    "    fig = plt.gcf()\n",
    "    fig.gca().add_artist(centre_circle)\n",
    "\n",
    "    # Equal aspect ratio ensures that pie is drawn as a circle\n",
    "    ax1.axis('equal')  \n",
    "    plt.title(plot_title, size=20)\n",
    "    plt.tight_layout()\n",
    "\n",
    "    plt.show()\n",
    "    #fig1.savefig(\"plots/{}\".format(plot_name), dpi=100)\n",
    "    \n",
    "dfe = df[df.result.notnull()]\n",
    "plot_code(dfe, \"Analysis result\", \"fin_result2.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "total = pd.merge(df,metadata,on='doi')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "6832"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(total)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge aggrigated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "agg = total.groupby(['doi']).success.max().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>doi</th>\n      <th>success</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>doi:10.7910/DVN/03CDTK</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>doi:10.7910/DVN/05BSPP</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>doi:10.7910/DVN/0BFF0K</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>doi:10.7910/DVN/0BPVCH</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>doi:10.7910/DVN/0DE35E</td>\n      <td>1.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                      doi  success\n0  doi:10.7910/DVN/03CDTK      NaN\n1  doi:10.7910/DVN/05BSPP      0.0\n2  doi:10.7910/DVN/0BFF0K      1.0\n3  doi:10.7910/DVN/0BPVCH      NaN\n4  doi:10.7910/DVN/0DE35E      1.0"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "1923"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(agg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "agg_total = pd.merge(agg, metadata, on='doi')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "1923"
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(agg_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "agg_total.to_csv('data/agg_total.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Drop if NaN or TLE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = total\n",
    "df_temp = df.drop(df[df.result.isnull() | (df['result'] == 'time limit exceeded')].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "0"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_temp.result.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "total = df_temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def success(el):\n",
    "    if pd.isna(el):\n",
    "        return el\n",
    "    if el == 'success':\n",
    "        return 1\n",
    "    if len(str(el))>1:\n",
    "        return 0\n",
    "    else:\n",
    "        el\n",
    "\n",
    "total['success']=total[\"result\"].apply(success)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "total.to_csv('data/total.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Journal "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "All journals' success rate: 0.42024253731343286\n"
    }
   ],
   "source": [
    "journals = total[total['type']==\"JOURNALS\"]\n",
    "print(\"All journals' success rate: \"+ str(journals.success.sum()*1./len(journals)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fix_name(el):\n",
    "    return el.split('Dataverse')[0].strip()\n",
    "\n",
    "def fix_name2(x):\n",
    "    if 'International Interactions (II)' in x:\n",
    "        return 'International Interactions (II)'\n",
    "    if 'American Journal of Political Science (AJPS)' in x:\n",
    "        return 'American Journal of Political\\nScience (AJPS)'\n",
    "    if 'British Journal of Political Science' in x:\n",
    "        return 'British Journal of\\nPolitical Science'\n",
    "    if 'American Political Science Review' in x:\n",
    "        return 'American Political\\nScience Review'\n",
    "    if 'Review of Economics and Statistics' in x:\n",
    "        return 'Review of Economics\\nand Statistics'\n",
    "    if 'Political Science Research and Methods (PSRM)' in x:\n",
    "        return 'Political Science Research\\nand Methods (PSRM)'\n",
    "    if 'Journal of Experimental Political Science' in x:\n",
    "        return 'Journal of Experimental\\nPolitical Science'\n",
    "    if 'International Studies Quarterly' in x:\n",
    "        return 'International\\nStudies Quarterly'\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "journals.name = journals.name.apply(fix_name)\n",
    "journals.name = journals.name.apply(fix_name2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>name</th>\n      <th>link</th>\n      <th>type</th>\n      <th>level</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>https://ajps.org/ajps-verification-policy/</td>\n      <td>verification</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>British Journal of\\nPolitical Science</td>\n      <td>https://www.cambridge.org/core/services/aop-fi...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>American Political\\nScience Review</td>\n      <td>https://www.apsanet.org/APSR-Submission-Guidel...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Review of Economics\\nand Statistics</td>\n      <td>https://www.mitpressjournals.org/journals/rest...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Political Science Research\\nand Methods (PSRM)</td>\n      <td>https://www.cambridge.org/core/journals/politi...</td>\n      <td>verification</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Journal of Experimental\\nPolitical Science</td>\n      <td>https://www.cambridge.org/core/journals/journa...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>International\\nStudies Quarterly</td>\n      <td>https://academic.oup.com/isq/pages/General_Ins...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>International Interactions (II)</td>\n      <td>https://www.tandfonline.com/action/authorSubmi...</td>\n      <td>encouraged</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>The Journal of Politics</td>\n      <td>https://www.journals.uchicago.edu/journals/jop...</td>\n      <td>no policy</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Political Analysis</td>\n      <td>https://www.cambridge.org/core/journals/politi...</td>\n      <td>reviewed</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Political Behavior</td>\n      <td>https://www.springer.com/journal/11109/submiss...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Research &amp; Politics</td>\n      <td>https://journals.sagepub.com/author-instructio...</td>\n      <td>required</td>\n      <td>3</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                                              name  \\\n0    American Journal of Political\\nScience (AJPS)   \n1            British Journal of\\nPolitical Science   \n2               American Political\\nScience Review   \n3              Review of Economics\\nand Statistics   \n4   Political Science Research\\nand Methods (PSRM)   \n5       Journal of Experimental\\nPolitical Science   \n6                 International\\nStudies Quarterly   \n7                  International Interactions (II)   \n8                          The Journal of Politics   \n9                               Political Analysis   \n10                              Political Behavior   \n11                             Research & Politics   \n\n                                                 link          type  level  \n0          https://ajps.org/ajps-verification-policy/  verification      5  \n1   https://www.cambridge.org/core/services/aop-fi...      required      3  \n2   https://www.apsanet.org/APSR-Submission-Guidel...      required      3  \n3   https://www.mitpressjournals.org/journals/rest...      required      3  \n4   https://www.cambridge.org/core/journals/politi...  verification      5  \n5   https://www.cambridge.org/core/journals/journa...      required      3  \n6   https://academic.oup.com/isq/pages/General_Ins...      required      3  \n7   https://www.tandfonline.com/action/authorSubmi...    encouraged      2  \n8   https://www.journals.uchicago.edu/journals/jop...     no policy      1  \n9   https://www.cambridge.org/core/journals/politi...      reviewed      4  \n10  https://www.springer.com/journal/11109/submiss...      required      3  \n11  https://journals.sagepub.com/author-instructio...      required      3  "
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# journal policy\n",
    "policy = pd.read_csv(\"data/journal-policy-survey.txt\", sep ='\\t')\n",
    "policy.name = policy.name.apply(fix_name2)\n",
    "policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "journal_policy = pd.merge(journals,policy,on='name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "1971"
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(journal_policy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#temp = temp[temp.type_y != \"no policy\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead tr th {\n        text-align: left;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr>\n      <th></th>\n      <th>name</th>\n      <th>publicationDate</th>\n      <th colspan=\"2\" halign=\"left\">success</th>\n      <th>s</th>\n    </tr>\n    <tr>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th>sum</th>\n      <th>count</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>2015</td>\n      <td>25</td>\n      <td>30</td>\n      <td>0.833333</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>2016</td>\n      <td>13</td>\n      <td>20</td>\n      <td>0.650000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>2017</td>\n      <td>53</td>\n      <td>67</td>\n      <td>0.791045</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>2018</td>\n      <td>24</td>\n      <td>54</td>\n      <td>0.444444</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>American Journal of Political\\nScience (AJPS)</td>\n      <td>2019</td>\n      <td>61</td>\n      <td>103</td>\n      <td>0.592233</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "                                            name publicationDate success  \\\n                                                                     sum   \n0  American Journal of Political\\nScience (AJPS)            2015      25   \n1  American Journal of Political\\nScience (AJPS)            2016      13   \n2  American Journal of Political\\nScience (AJPS)            2017      53   \n3  American Journal of Political\\nScience (AJPS)            2018      24   \n4  American Journal of Political\\nScience (AJPS)            2019      61   \n\n                s  \n  count            \n0    30  0.833333  \n1    20  0.650000  \n2    67  0.791045  \n3    54  0.444444  \n4   103  0.592233  "
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = journal_policy\n",
    "temp = temp.groupby(['name','publicationDate']).agg({'success': ['sum','count']}).reset_index()\n",
    "temp['s']=temp['success']['sum'] / temp['success']['count']\n",
    "temp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = temp.pivot(columns='name', index='publicationDate', values='s').reset_index()\n",
    "#df.fillna(0.0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 864x648 with 12 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df= temp\n",
    "g = sns.FacetGrid(df, col='name', hue='name', col_wrap=4, )\n",
    " \n",
    "# Add the line over the area with the plot function\n",
    "g = g.map(plt.plot, 'publicationDate', 's')\n",
    " \n",
    "# Fill the area with fill_between\n",
    "g = g.map(plt.fill_between, 'publicationDate', 's', alpha=0.2).set_titles(\"{col_name}\")\n",
    " \n",
    "# Control the title of each facet\n",
    "g = g.set_titles(\"{col_name}\")\n",
    " \n",
    "# Add a title for the whole plo\n",
    "#plt.subplots_adjust(top=0.92)\n",
    "#g = g.fig.suptitle('Evolution of the value of stuff in 16 countries')\n",
    "\n",
    "#fig.tight_layout()\n",
    "#fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "ag_journals = agg_total[agg_total['type']==\"JOURNALS\"]\n",
    "ag_journals = ag_journals.drop(ag_journals[ag_journals.success.isnull()].index)\n",
    "\n",
    "ag_journals.name = ag_journals.name.apply(fix_name)\n",
    "ag_journals.name = ag_journals.name.apply(fix_name2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "Aggregated all journals' success rate: 0.4729381443298969\n"
    }
   ],
   "source": [
    "print(\"Aggregated all journals' success rate: \"+ str(ag_journals.success.sum()/len(ag_journals)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "ag_journal_policy = pd.merge(ag_journals,policy,on='name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# temp = temp[temp.type_y != \"no policy\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = ag_journal_policy\n",
    "temp = temp.groupby(['name','publicationDate','type_y']).agg({'success': ['sum','count']}).reset_index()\n",
    "temp['s']=temp['success']['sum'] / temp['success']['count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "pal = sns.color_palette(\"nipy_spectral\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 864x648 with 12 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df= temp\n",
    "g = sns.FacetGrid(df, col='name', hue='name', col_wrap=4, )\n",
    " \n",
    "# Add the line over the area with the plot function\n",
    "colors = {\"no policy\": pal[4], \"encouraged\": pal[3], \"required\": pal[2], \"reviewed\": pal[1], \"verification\": pal[0]} \n",
    "g = g.map(plt.plot, 'publicationDate', 's')\n",
    " \n",
    "# Fill the area with fill_between\n",
    "g = g.map(plt.fill_between, 'publicationDate', 's', alpha=0.2).set_titles(\"{col_name}\")\n",
    " \n",
    "# Control the title of each facet\n",
    "g = g.set_titles(\"{col_name}\")\n",
    " \n",
    "# Add a title for the whole plo\n",
    "#plt.subplots_adjust(top=0.92)\n",
    "#g = g.fig.suptitle('Evolution of the value of stuff in 16 countries')\n",
    "\n",
    "#fig.tight_layout()\n",
    "#g.savefig(\"over_time.png\")\n",
    "#fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aggregated results plotted per policy type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = ag_journal_policy\n",
    "temp = temp.groupby(['publicationDate','type_y']).agg({'success': ['sum','count']}).reset_index()\n",
    "temp['s']=temp['success']['sum']*100. / temp['success']['count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": "<Figure size 1080x216 with 5 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df= temp\n",
    "#g = sns.FacetGrid(df, col='type_y', hue='type_y', col_wrap=5, )\n",
    "g = sns.FacetGrid(\n",
    "    df[(df['publicationDate']<2020) & (df['publicationDate']>2015)], col='type_y', hue='type_y', col_wrap=5, )\n",
    "\n",
    "\n",
    "# Add the line over the area with the plot function\n",
    "colors = {\"no policy\": pal[4], \"encouraged\": pal[3], \"required\": pal[2], \"reviewed\": pal[1], \"verification\": pal[0]} \n",
    "g = g.map(plt.plot, 'publicationDate', 's')\n",
    " \n",
    "# Fill the area with fill_between\n",
    "g = g.map(plt.fill_between, 'publicationDate', 's', alpha=0.2).set_titles(\"{col_name}\")\n",
    " \n",
    "# Control the title of each facet\n",
    "g = g.set_titles(\"{col_name}\")\n",
    " \n",
    "# Add a title for the whole plo\n",
    "#plt.subplots_adjust(top=0.92)\n",
    "#g = g.fig.suptitle('Evolution of the value of stuff in 16 countries')\n",
    "\n",
    "#fig.tight_layout()\n",
    "#g.savefig(\"policy_type.png\")\n",
    "#plt.title(\"Success rate per policy type from 2016 to 2019\")\n",
    "#fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# temp.pivot(columns='success', index='name', values='publicationDate')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Journal per year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "array(['ajps', 'BJPolS', 'jop', 'restat', 'pan', 'ipsr-risp',\n       'the_review', 'LAPS', 'PSRM', 'isq', 'IOJ', 'lsq', 'xps',\n       'researchandpolitics', 'world-politics', 'JPublicPolicy',\n       'perspectives', 'internationalinteractions', 'culturalanalytics',\n       'economics', 'polbehavior', 'FPA', 'JAERE', 'bpsr', 'ps', 'qje',\n       'jhr', 'tpmnewsletter', 'palcomms', 'jlc', 'isec', 'JJPS', 'cjip'],\n      dtype=object)"
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "journals.publisher.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "top = [\n",
    "    'jop', 'ajps', 'PSRM', 'BJPolS', 'pan', 'isq','IOJ','culturalanalytics','JPublicPolicy',\n",
    "    'the_review','polbehavior','restat','internationalinteractions','xps','researchandpolitics']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "journals_subset = journals.drop(journals[~journals.publisher.isin(top)].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = journals_subset\n",
    "temp = temp.groupby(['name','publicationDate']).agg({'success': ['sum','count']}).reset_index()\n",
    "temp['s']=temp['success']['sum']*100. / temp['success']['count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 1080x648 with 15 Axes>"
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     "metadata": {
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   ],
   "source": [
    "df= temp\n",
    "g = sns.FacetGrid(df, col='name', hue='name', col_wrap=5, )\n",
    " \n",
    "# Add the line over the area with the plot function\n",
    "colors = {\"no policy\": pal[4], \"encouraged\": pal[3], \"required\": pal[2], \"reviewed\": pal[1], \"verification\": pal[0]} \n",
    "g = g.map(plt.plot, 'publicationDate', 's')\n",
    " \n",
    "# Fill the area with fill_between\n",
    "g = g.map(plt.fill_between, 'publicationDate', 's', alpha=0.2).set_titles(\"{col_name}\")\n",
    " \n",
    "# Control the title of each facet\n",
    "g = g.set_titles(\"{col_name}\")"
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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